1. Field of the Invention
The present invention relates to a method for detecting circles, and more particularly a method for detecting circles in an image using horizontal and vertical scanning.
2. Description of Prior Art
Detecting a circle in an image is a basic task needed for computer vision, for example, in Surface Mounted Device (SMD) inspection applications. Typically, a Hough transform is used for computerized circle and curve detection. The principle of the Hough transform is to detect parameterized curves by mapping image edge pixels into manifolds in a parameter space and finding peaks using a multidimensional histogram procedure. This method, however, is expensive in terms of computation and memory needs. Typically, due to memory storage limitations, this method also has discretization error in both the image and the parameter space.
Recently, several methods have been proposed to improve Hough transform techniques in terms of efficiency, accuracy and memory storage. One modified scheme uses gradient orientation from edge points. The probablisitic Hough transform attempts to reduce redundant information by sampling image data in various ways. The randomized Hough transform is proposed to detect a curve with n parameters by randomly picking n pixels and mapping them into one point in the parameter space, instead of transforming one pixel into a hyperplan in n-dimensional parameter space. Other methods, such as the generalization Hough transform and the decomposed Hough transform, have been proposed to improve Hough transform techniques. However, the above-mentioned methods are Hough transformation based and are therefore, generally slow.
Therefore, a need exists for a fast, accurate, and robust method of dominant circle and ring detection in a given region without transforms (needing less memory).